SDN Node Update via Alpha-Beta Propagation
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Solution Overview
Problem
Current software-defined networks face bottlenecks in updating software across large numbers of nodes, leading to prolonged update times, state issues due to mixed software versions, and single-point failures in file transfer, especially in geographically distributed networks.
Innovation Solution
Implementing a method where a first set of 'Alpha' nodes is selected and updated, then used to propagate updates to 'Beta' nodes, which can subsequently become 'Alpha' nodes, distributing the update process and reducing reliance on a single centralized engine, thereby enhancing redundancy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a centralized engine is used to push software updates to all nodes, then update control is centralized and simple, but update time becomes extremely long for large networks and a bottleneck is created
Solution Approach 1:
The network is segmented into multiple zones or regions, and update propagation is divided into phases where Alpha nodes update first, then serve as sources for Beta nodes. This segmentation allows parallel update propagation across different network segments, dramatically improving update speed while maintaining controlled complexity through hierarchical management.
Solution Approach 2:
Alpha nodes are pre-selected and pre-configured with update capabilities before the update process begins. These nodes are prepared in advance to serve as distribution points, allowing the update process to start immediately without waiting for sequential propagation from the centralized engine to every node.
2Device complexity
If a single centralized engine pushes updates, then update distribution is simple to manage, but the system creates a single point of failure with no redundancy
Solution Approach 1:
Alpha nodes act as intermediary distribution points between the centralized engine and Beta nodes. This intermediary layer distributes the reliance away from the single centralized engine, creating redundant update paths. If the centralized engine fails, Alpha nodes that have already received updates can continue propagating them to Beta nodes independently.
Solution Approach 2:
The update distribution function is segmented between the centralized engine (which updates Alpha nodes) and the Alpha nodes themselves (which update Beta nodes). This segmentation creates multiple independent update sources, eliminating the single point of failure while the centralized engine maintains overall coordination simplicity.
3Stability of the object's composition
If all nodes are updated simultaneously from a centralized source, then update consistency is maintained, but network bandwidth is overwhelmed and update time increases
Solution Approach 1:
The node population is segmented into Alpha and Beta groups with different update roles. Alpha nodes receive updates first and serve as local distribution points, while Beta nodes receive updates from their nearest Alpha nodes. This segmentation creates multiple localized update streams that don't compete for centralized bandwidth, improving overall throughput while maintaining version consistency through coordinated phase transitions.
Solution Approach 2:
The update propagation is moved from a single-dimensional centralized model to a two-dimensional distributed model, where updates flow both from the centralized engine to Alpha nodes and from Alpha nodes to Beta nodes in parallel. This dimensional change enables concurrent update operations across multiple network paths, dramatically increasing throughput without sacrificing consistency.
4Adaptability or versatility
If mixed software versions exist across nodes, then gradual adaptation is possible, but state issues and network conflicts arise
Solution Approach 1:
The update process is divided into periodic phases: Phase 1 updates Alpha nodes while Beta nodes remain on the old version; Phase 2 updates Beta nodes using Alpha nodes as sources. This periodic, phased approach allows gradual adaptation while maintaining network functionality throughout. Version conflicts are minimized because each phase transitions a specific subset of nodes, and the system is designed to handle the expected version mix at each phase boundary.
Data Source
AI summary
A method may include identifying an update file for a plurality of nodes; selecting a first set of nodes of the plurality of nodes based on a set of node selection criteria; sending the update file to the first set of nodes via a software-defined network (SDN); receiving a first message from a first node of the first set of nodes indicating that the first node is ready to host the update file; identifying a second node that is connected to the first node responsive to receiving the first message from the first node; sending a first instruction to the second node for the second node to obtain the update file from the first node; receiving a second message from the second node indicating that the second node is ready to host the update file; and adding the second node to the first set of nodes.